TYPE,NAME,INFOHASH,SIZEBYTES,MIRRORS,DOWNLOADERS,TIMESCOMPLETED,DATEADDED,DATEMODIFIED
Dataset,"Crater Dataset",30748b1a7ac99b1c5ff66f0bc5c5f7428ed035c5,32489372,7,0,2024,1386737396,1386737396
Dataset,"Visual Object Classes Challenge 2012 Dataset (VOC2012) VOCtrainval_11-May-2012.tar",df0aad374e63b3214ef9e92e178580ce27570e59,1999639040,8,0,3156,1387492795,1387492795
Dataset,"UCI Machine Learning Datasets 12/2013",7fafb101f9c7961f9b840daeb4af43039107ddef,16365432846,7,0,11205,1387533625,1387533625
Dataset,"Arizona State University Twitter Data Set",2399616d26eeb4ae9ac3d05c7fdd98958299efa9,354770146,16,0,14798,1387775825,1387775825
Dataset,"THEMIS Day IR Global Mosaic",8b202f57d4bf3304c10fcd11bdee224c3a9ff16f,4391605981,15,0,15515,1388168230,1388168230
Dataset,"MOLA Shaded Relief / Colorized Elevation",06f73b5ca501194ba1cd3aa918bd801b84ea7050,2767208648,10,0,9822,1388168408,1388168408
Dataset,"Viking Merged Color Mosaic",059ed25558b4587143db637ac3ca94bebb57d88d,276679753,13,0,15794,1388169030,1388169030
Dataset,"NLCD2006 Land Cover Change (NLCD2006_landcover_change_pixels_5-4-11_se5.zip)",28a2fd1afbda8be43bec55b6c4c2c9cf1f5b9582,104431285,7,0,9608,1390274676,1390274676
Dataset,"Viking MDIM2.1 Colorized Global Mosaic 232m",c746fd3441d19772627fd36599dc418241d39452,12740265271,6,0,9422,1394139848,1394139848
Dataset,"Twitter Data - NIPS 2012",046cf7a75db2a530b1505a4ce125fbe0031f4661,22339604,14,0,8415,1396817544,1599249522
Dataset,"Wikipedia English Official Offline Edition 2014-02-03",9512a1f6d21e5012c06a1c9b8e2dd4796ecc77a9,10587333911,3,0,2134,1398706232,1599249524
Dataset,"BU-Web-Client Network Traces",f305fe91840e1e117bdf27bd6c3970a69d90b92f,13786856,10,0,10124,1400273176,1599249391
Dataset,"LBL-CONN-7 Network Traces",2060d7faa61dd774f9279be7f3f79cece12ed0ed,15575483,11,0,5791,1400273567,1599249493
Dataset,"UMN Sarwat Foursquare Dataset (September 2013)",b24c73949308b3f6bdd8fea1a485534392eef338,160746527,5,0,2283,1404328916,1599249440
Dataset,"US domestic flights from 1990 to 2009",a2ccf94bbb4af222bf8e69dad60a68a29f310d9a,35404022,7,0,8396,1407700944,1599249494
Dataset,"Lerman Twitter 2010 Dataset",d8b3a315172c8d804528762f37fa67db14577cdb,292173969,11,0,3376,1408132374,1599249628
Dataset,"Lerman Digg 2009 Dataset",d98540da6d34fb6a0150fd88b41580a377cb454d,37554853,6,0,4182,1408133472,1599249520
Dataset,"Mnih Massachusetts Building Dataset",630d2c7e265af1d957cbee270f4328c54ccef333,2074077884,9,0,6463,1411154157,1599249501
Dataset,"Object and Concept Recognition for Content-Based Image Retrieval (CBIR)",d5d80c1ad9d6b44b6e80c942414f1753bf9a1970,387885021,4,0,2353,1411422756,1599249233
Dataset,"MPEG-7 Core Experiment CE-Shape-1 [tar.gz]",0a8cb3446b0de5690fee29a2c68922ff691c7f9a,2268576,11,0,4790,1412802896,1599249217
Dataset,"NLCD2006 Land Cover (2011 Edition) nlcd_2006_landcover_2011_edition_2014_03_31.zip",081cae4ec8ce93a6b86ea1b55a4cca113a257593,1093422220,6,0,5142,1412809006,1599249673
Dataset,"MNIST Database",ce990b28668abf16480b8b906640a6cd7e3b8b21,11594722,12,0,3955,1413247283,1599249619
Dataset,"The Extended Yale Face Database B (Cropped)",aad8bf8e6ee5d8a3bf46c7ab5adfacdd8ad36247,58493820,8,0,7759,1413836352,1599249492
Dataset,"The Extended Yale Face Database B",06e479f338b56fa5948c40287b66f68236a14612,2086248732,18,0,17059,1413838384,1599249435
Dataset,"20150112.json.gz",466d6a3794328acc7c068a45f0380ef3ade8345f,3908362534,5,0,6260,1421493965,1599249560
Dataset,"A collection of sport activity files for data analysis and data mining",aac04fca4cd3b4dcd580e9018d68fa0647b7d908,316182217,4,0,2381,1424092450,1599249647
Dataset,"UCI Folio Leaf Dataset",a6c64db1e42721f5d7e7aa2b118e293a0d0d335b,972471245,4,0,5539,1444657270,1599249453
Dataset,"Georgia Tech face database",0848b2c9b40e49041eff85ac4a2da71ae13a3e4f,133192489,22,0,5914,1446147062,1599249649
Dataset,"Boston Hubway Data Visualization Challenge Dataset",3e395a74e333156daddcd67d614415fc9e237340,25999914,6,0,2519,1448329142,1599249408
Dataset,"Columbia University Image Library (COIL-20)",1d16994c70b7fff8bfe917f83c397b1193daee7f,19894476,8,0,238,1448573399,1599249493
Dataset,"Structured Web Data Extraction Dataset (SWDE)",411576c7e80787e4b40452360f5f24acba9b5159,207314582,6,0,2692,1448821899,1646338703
Dataset,"A collection of sport activity files for data analysis and data mining 2016a",af55533bf8229c3bff260b77a652f8b8058f6c9e,245469985,5,0,8337,1453126055,1599249488
Dataset,"Vincent van Gogh Paintings",c8b687c984d3d902310f27d56759ed69f5e1b4a7,513763028,22,0,16019,1453667237,1599249439
Dataset,"NYPD 7 Major Felony Incidents",5c195d570d910402727638f4ba123d171694fbdc,13233486,5,0,2739,1454346901,1599249497
Dataset,"BuzzFeed News transcription of Airbnb NYC data",968a3ff5e4182cdecd239980ecfd257a37451003,192919,8,0,2269,1454347477,1599249501
Dataset,"Labeled Fishes in the Wild",41bc10c77d54b49fb0a96ff5d4a0814bc2ab7da7,444365962,9,0,7069,1454531235,1599249480
Dataset,"Terrestrial Ecological Systems of the United States (Version 3.0; Updated March 2014)",f1f67ca3faef718afcc35a530eebbd72c20b0eac,3988579396,3,0,949,1454617076,1599249295
Dataset,"Educational Process Mining (EPM): A Learning Analytics Data Set Data Set",e24e083cc337695bb84a2b68707695579c0ab4d8,4934446,15,0,10357,1455204482,1599249464
Dataset,"Online News Popularity Data Set",95d3b03397a0bafd74a662fe13ba3550c13b7ce1,7476401,7,0,3042,1455204739,1599249426
Dataset,"Yelp Restaurant Photo Classification Data",19c3aa2166d7bfceaf3d76c0d36f812e0f1b87bc,14135506706,3,0,721,1463020013,1599249519
Dataset,"QuantQuote Free Historical Stock Data 2013",49daf05ef35c487331013c22450988bbf7e511b0,36616638,5,0,623,1466459308,1599249648
Dataset,"ISBI Challenge: Segmentation of neuronal structures in EM stacks",42714f859770f1a9d8b27985f9f16ea17e8ba2f6,23611963,3,0,1363,1467409293,1599249431
Dataset,"Enron Email Dataset",4697a6e1e7841602651b087d84f904d43590d4ff,443254787,14,0,6270,1472183402,1599249364
Dataset,"Sentiment Labelled Sentences Data Set",07e05fc1229555e124df72160a01b2540d04cebf,512208,6,0,493,1472183802,1599249653
Dataset,"True Marble Global Image Dataset GeoTIFF",b9b284d9c0074846fee28e78aac4440fd7c0f51c,9737051000,6,1,979,1472237761,1599249639
Dataset,"Avantes Dual Spectrograph.zip",ff051a9469c9ceda93ea914a21639a639cbae793,21477445031,3,0,63,1472579261,1599249524
Dataset,"The Cars Overhead With Context (COWC)",210dfc51f11dcfced602ad226962b7590e08c50a,9338326203,3,0,547,1474414392,1599249453
Dataset,"Gland Segmentation in Histology Images Challenge (GlaS) Dataset",208814dd113c2b0a242e74e832ccac28fcff74e5,180902609,9,0,531,1474493147,1599249431
Dataset,"UCSD Pedestrian Database",fed43599b7e8e0a0fbe1e22062cdb54d36cf951d,791870738,3,0,144,1474494273,1599249546
Dataset,"Modified PubMed Dataset used by WSU-IR team at TREC 2015 Clinical Decision Support Track",371a9244d2e9344a196a449f898e0a4385b6b43a,18533878946,4,0,87,1474744359,1599249408
Dataset,"A collection of IRONMAN, IRONMAN 70.3 and Ultra-triathlon race results",2269d7d1c77375aea732eea0905e370d4741575f,54957988,6,0,1513,1475226544,1599249499
Dataset,"Udacity Self-Driving Car Dataset 2-1",f2666220bb74417dfc43815b710a1565cd1a6b76,1637815137,5,0,1670,1476135427,1599249512
Dataset,"Udacity Self-Driving Car Dataset 2-2",bcde779f81adbaae45ef69f9dd07f3e76eab3b27,7043569975,3,0,442,1476136348,1599249453
Dataset,"Udacity Self-Driving Car Driving Data 9/29/2016 (dataset.bag.tar.gz)",6011d0e932970efc999809e9cafab8e791c93bb8,25950077103,3,0,727,1476139849,1599249524
Dataset,"Udacity Dataset 2-3 Compressed",1d7fa5116a809b1537bf521fd19897de5d69b7a3,20961890219,4,0,1045,1476231965,1599249492
Dataset,"MNIST Database (mnist.pkl.gz)",323a0048d87ca79b68f12a6350a57776b6a3b7fb,16168813,10,0,860,1476242192,1599249500
Dataset,"vgg19_normalized.pkl",854efbd8e2c085e8e0e5fb2d254ed0e21da6008e,80126892,3,0,89,1476301011,1599249174
Dataset,"Udacity Self Driving Car Dataset 3-1: El Camino",c9dae89d2e3897e6aa98c0c8196348c444998a2a,29994697505,3,0,517,1477015673,1599249431
Dataset,"MovieLens 20M Dataset",296054417b4d8eeeb4c7b1c842570bf792ee4d14,198702078,8,0,1755,1481900699,1599249510
Dataset,"AOL Search Data 20M web queries (2006)",cd339bddeae7126bb3b15f3a72c903cb0c401bd1,460409936,5,0,483,1482001740,1599249352
Dataset,"US Stock Market End of Day dataset",c5a49e46249fef6a3219919fef96fd0265da4d3a,250708117,6,0,1267,1482557996,1599249643
Dataset,"Microsoft Academic Graph - 2016/02/05",1e0a00b9c606cf87c03e676f75929463c7756fb5,28942081611,4,0,245,1482698542,1599249500
Dataset,"Pre-configured (Mint) linux based virtual machine image",5ceb6902b46a344de6db18c2ec5a14bb24a7df4a,3062967296,3,0,269,1483643998,1599249431
Dataset,"Open Payments Dataset - 2013 Program Year",92a1aeaaf741f3d1669ad0f0186d96ec168ee550,277982372,8,0,118,1488126519,1599249654
Dataset,"Open Payments Dataset - 2014 Program Year",88f6fff84d7c2a2769348ab4c2b0ecb318b43752,728444845,7,0,243,1488127301,1599249514
Dataset,"Open Payments Dataset - 2015 Program Year",de413718a03cd670535c772cf68116775a9e2537,584875180,3,0,215,1488127788,1599249501
Dataset,"Wikilinks: A Large-scale Cross-Document Coreference Corpus Labeled via Links to Wikipedia (Original Dataset)",beefa2ec4161432cd1d9f693a88d3670aae68357,1837946933,3,0,196,1488651083,1599249419
Dataset,"Udacity Didi $100k Challenge Dataset 1",76352487923a31d47a6029ddebf40d9265e770b5,32801992154,3,0,939,1490234857,1599249515
Dataset,"A collection of sport activity datasets for data analysis and data mining 2017a",f2221a292540ff3e6c85025754f775361c7cd886,789140302,4,0,845,1490876261,1599249502
Dataset,"VGG Cell Dataset from Learning To Count Objects in Images",b32305598175bb8e03c5f350e962d772a910641c,16339802,8,0,285,1491094963,1599249373
Dataset,"Didi Data Release #2 - Round 1 Test Sequence and Training",18d7f6be647eb6d581f5ff61819a11b9c21769c7,21929778522,3,0,543,1491329535,1599249500
Dataset,"Human acute monocytic leukemia",8464b9f9166c143040fee655f0284085fe251a80,1609437908,7,0,145,1493422482,1599249263
Dataset,"Downsampled ImageNet 64x64",96816a530ee002254d29bf7a61c0c158d3dedc3b,12589844480,12,1,3222,1496447815,1599249237
Dataset,"Downsampled ImageNet 32x32",bf62f5051ef878b9c357e6221e879629a9b4b172,4274493440,16,0,3571,1496455779,1599249522
Dataset,"Small Object Dataset",8e751c111cf90123374b5f0cf61e6af9f5e5231e,5858609,8,0,763,1496780885,1599249471
Dataset,"New York Taxi Data 2009-2016 in Parquet Fomat",4f465810b86c6b793d1c7556fe3936441081992e,35078948106,6,0,927,1498931213,1599249475
Dataset,"AVA: A Large-Scale Database for Aesthetic Visual Analysis",71631f83b11d3d79d8f84efe0a7e12f0ac001460,33142609854,12,0,13631,1500205149,1599249526
Dataset,"N+1 fish, N+2 fish dataset (test_videos)",6fc9279d862d4f6e42ec2613c5b5ceea165cff00,32929954363,2,0,104,1504707336,1599249505
Dataset,"NIH Pancreas-CT Dataset",80ecfefcabede760cdbdf63e38986501f7becd49,4863883044,20,0,17557,1505241389,1599249505
Dataset,"Ischemic Stroke Lesion Segmentation Challenge 2017 (ISLES2017)",5bdb401695ad36d4ccd73da90c2f9f8ab6f82092,1403654243,9,0,1189,1505317133,1599249408
Dataset,"Non-Small Cell Lung Cancer CT Scan Dataset (NSCLC-Radiomics-Genomics)",95b58ebfc1952780cfe2102dd7290889feefad66,4522256159,11,0,515,1505841529,1599249224
Dataset,"MICCAI 2015 Challenge on Multimodal Brain Tumor Segmentation (BraTS2015)",c4f39a0a8e46e8d2174b8a8a81b9887150f44d50,5340438240,9,0,686,1505842084,1599249233
Dataset,"NIH Chest X-ray Dataset of 14 Common Thorax Disease Categories",557481faacd824c83fbf57dcf7b6da9383b3235a,45089461497,15,0,4585,1507562340,1599249439
Dataset,"UC Merced Land Use Dataset",e9ac5edf285a43309e57e1289e8816a4e78a937c,332468434,6,0,194,1507649570,1599249490
Dataset,"UrbanMapper 3D (Digital Surface Model and Digital Terrain Model) Dataset",4ccd3743861d827ac80f0d2b234d7fcfdad2a31d,6618441904,6,0,179,1507998032,1676410024
Dataset,"Animals with Attributes 2 (AwA2) dataset",1490aec815141cdb50a32b81ef78b1eaf6b38b03,13923921135,9,0,441,1508761603,1599249508
Dataset,"Electron Microscopy (CA1 hippocampus) Dataset",3ada3ae6ec71097e63d897cf878051bba3eaba25,3873351785,12,0,214,1508839502,1599249629
Dataset,"GANGogh training data set",1d154cde2fab9ec8039becd03d9bb877614d351b,37153345191,3,0,894,1511915640,1599249511
Paper,"Genetically Enhanced Feature Selection of Discriminative Planetary Crater Image Features",cb1655a57dd24345c9ea7a43c5ec09e03c7a0979,580959,1,0,2468,1385225939,1385225939
Paper,"Mars Weekend: A Panel and Games at the Museum of Science Boston",b0700675b5b7756ba6243420a9db09380a5d27b2,146895,3,0,2038,1385226344,1385226344
Paper,"Effectiveness of Cybersecurity Competitions",30ec3bb79d95e4af3b92315a5a073fb10ec8a87d,318479,7,0,2257,1385350009,1385350009
Paper,"Bernoulli trials based feature selection for crater detection",37499de2b944dacc88cd295d3f9631670bd6abe6,2379301,4,0,1977,1386738024,1386738024
Paper,"Crater Detection via Genetic Search Methods to Reduce Image Features",8ae530c0c1466ba8feee9914236cc900ad2f708e,19307248,5,0,2910,1387131834,1387131834
Paper,"New approach for modeling of transiting exoplanets for arbitrary limb-darkening law",bbf1c32bd69459b93742eb691bf11fc8961e6db7,3576941,3,0,1644,1391251336,1391251336
Paper,"Efficient Accelerometer-based Event Detector in Wireless Sensor Networks",b0fc43009de3d358bfbd8a14ba99ca320b356bc5,516709,2,0,1680,1391274197,1391274197
Paper,"Accelerometer-Based Event Detector for Low-Power Applications",4bee3aad417a4670079da4daf129d5e4708f61d4,1452817,2,0,2270,1391274519,1391274519
Paper,"Introducing R",d430724be7ac00f4b5e7f0d956f8411ef9b67dbe,820994,10,0,4741,1391492723,1391492723
Paper,"Management of acute and post-operative pain in chronic kidney disease",f92f4798efd078afe1708efb74a3816a66a23104,571347,2,0,1564,1391796458,1391796458
Paper,"Analysis of the Cryptocurrency Marketplace",daaa86689c42e78c4111b74984d5036a426f6cf6,1977999,125,3,3829,1393146378,1393146378
Paper,"Introduction to Theory of Computation",d746df46e76fcfdb8e0b682a5e47ed1a776db7db,1292372,3,0,2911,1396187783,1599249259
Paper,"A general method applicable to the search for similarities in the amino acid sequence of two proteins",8c6a6a95236461d9e249a820a6d67cf3dbf13dc0,641724,7,0,1704,1414619817,1599249516
Paper,"A Brief Review of Nature-Inspired Algorithms for Optimization",aec97f8374cfa5b8bce86cd542870fe849e1afb5,161539,3,0,1495,1483954281,1599249431
Course,"Caltech CS156 - Machine Learning - Yaser",8190b5122515ab158cd29ccdb33ea946a3e529f4,3358232906,16,0,10384,1429908094,1599249260
Course,"Stanford EE364A - Convex Optimization I - Boyd",393dc896234b96a1cd251c14cfc65d2ff594d6e9,4458038066,10,0,2310,1429930458,1599249592
Course,"[Coursera ] Text Mining and Analytics",e2c129491a3841bfac5d7b08b41ad79387132a23,1063576833,12,0,5214,1485074956,1599249646
Course,"[Coursera] Algorithms: Design and Analysis, Part 1 (Stanford University) (algo)",7bfcfbaf2c53588b23ba1ebccae47a2b9c5197b7,1948909326,15,0,14885,1488677043,1599249295
Course,"Integrative Biology 131 - General Human Anatomy Online Course Videos - UCBerkeley",5a0d6b38ab0adb9e52182164ffa8db19822f73ef,8524375550,12,0,3617,1488992136,1599249413
Course,"Electrical Engineering 123, 001 - Spring 2015 - UC Berkeley",530416f4f3a4b2cac90e61d5df72d1610dec68b4,6058044588,16,0,4089,1489015679,1599249664
Course,"Public Health 150E, 001 - Spring 2015 - UC Berkeley",057e7009bdf9e3d09b1ef56ffbd82a1d1a5de23c,252003485,10,0,1366,1489030422,1599249664
Course,"Bioengineering 200, 001 - Spring 2014 - UC Berkeley",c4cd3183550f9cc1cfdcb69f15b076ba439ee062,3801748047,10,0,2322,1489043753,1599249453
Course,"Astronomy C12, 001 - Fall 2014 - UC Berkeley",1433dd89d4366df2b534c5e3b6b267776a67e7af,11353991797,15,0,1627,1489045227,1599249371
Course,"Nuclear Engineering 101, 001 - Fall 2014 - UC Berkeley",92644e4132e893c70c3e0ad9ac1d58bef554bd14,4967134337,10,0,2585,1489046829,1599249664
Course,"Environmental Economics and Policy 145 - Fall 2014 - UC Berkeley",c633df0181d560050d3f392501c6815135cfb60e,3926455147,9,0,1846,1489076046,1599249519
Course,"Psychology 1 - General Psychology - Fall 2007 - UC Berkeley",687bfcdf88598c04edf98c56c3b5f838d43ec2a6,3362583340,22,0,7132,1489077507,1599249516
Course,"Chemical & Biomolecular Engineering 179 Process Technology of Solid-State Materials Devices - UC Berkeley",f1baa15065060f1830d74111c1ef7741a73c9e98,3641717107,13,0,2637,1489078608,1599249512
Course,"Physics 10, 001 - Spring 2006 - UC Berkeley",5140da14dd72b2a6f19a5ca08d2e2d015754909a,4820005717,14,0,3721,1489078706,1599249495
Course,"Economics 1, 001 - Fall 2011 - UC Berkeley",93628c9e317768a5bf994eec845834d9e4a749e9,4186156273,11,0,4617,1489080675,1599249469
Course,"Chemistry 3B, 002 - Fall 2014 - UC Berkeley",769ef081e79307987fd52ed97c82fe7c590c88f8,4788602900,8,0,1966,1489081332,1599249627
Course,"Chemistry 1A, 002 - Spring 2010 - UC Berkeley",ebe62de0d85ba9563c566cc5b082416792bc00ca,9283464842,15,0,2867,1489087005,1599249240
Course,"Political Science 179 - Spring 2008 - UC Berkeley",e75a329db4adabdc45502c401a1c4b69712cbb98,1496266068,9,0,3899,1489094013,1599249423
Course,"Multivariable Calculus - Math 53 - Fall 2009 - UC Berkeley",d90733721eb2a2ba839434decce91ce4803cbf1e,5840425737,17,1,3467,1489094285,1599249660
Course,"International and Area Studies 107, 001 - Spring 2011 - UC Berkeley",97e704bba2ad3fb2dc5d932f4ed693fcb2f85b30,1643354598,7,0,3350,1489096669,1599249324
Course,"Statistics 21 - Fall 2009 - UC Berkeley",4d505fe0b3cbcbeff32bfd7b75a783f900dc8c6d,4268779318,14,0,7859,1489096997,1599249372
Course,"Statistics 21 - 001 - Spring 2010 - UC Berkeley",56b38a7013673c92cb951eb79bcd3a26e8158095,5575307389,13,0,5461,1489097108,1599249650
Course,"Peace and Conflict Studies 164B - Spring 2007 - UC Berkeley",0ec86c151be43be4857e2da370fb5508ff418146,5065283796,8,0,2315,1489097374,1599249618
Course,"Law 271, Environmental Law and Policy - Fall 2009 - UC Berkeley",c878ea12eff8c99cc6b1983a2d7724a18bb1a94d,4253328680,8,0,1555,1489104935,1599249431
Course,"Public Health 241, 001 - Spring 2011 - UC Berkeley",8469a366bf4b71ff62d9e2327537771bdc145dfa,1874365386,9,0,4933,1489105012,1599249432
Course,"Richard Feynman's Lectures on Physics (The Messenger Lectures)",c5af268ec55cf2d3b439e7311ad43101ba8322eb,1073900292,31,0,32633,1500582842,1599249511
Course,"Introduction to Computer Science [CS50x] [Harvard] [2018]",52da574b6412862e199abeaea63e51bf8cea2140,9605502232,62,0,58332,1516791534,1599249665
Dataset,"Breast Cancer Cell Segmentation",b79869ca12787166de88311ca1f28e3ebec12dec,159955958,8,0,1470,1519069114,1599249262
Dataset,"Malignant lymphoma classification",3cde17e7e4d9886513630c1005ba20b8d37c333a,1441583313,12,0,6746,1519070265,1599249392
Dataset,"A collection of sport activity datasets with an emphasis on powermeter data",bf76b193960a96a683f9c2afde70acab9d3d757d,919751720,13,0,2050,1529744925,1599249639
Dataset,"LUng Nodule Analysis (LUNA16) All Images",58b053204337ca75f7c2e699082baeb57aa08578,65995402313,10,0,3233,1531673350,1599249506
Dataset,"Corpus of Russian news articles collected from Lenta.Ru",cfc4ba252fe56176d9db31b0609f0ece6a389b09,1810139847,5,0,131,1531775000,1599249544
Dataset,"North America roads GIS data",0a853fdcc1d28c306d75e29195a5536087f6e2b4,8353311760,4,0,130,1532180893,1599249259
Dataset,"LiTS – Liver Tumor Segmentation Challenge (LiTS17)",27772adef6f563a1ecc0ae19a528b956e6c803ce,16655115138,19,0,10148,1532208088,1599672269
Dataset,"VizWiz v1.0 dataset (Answering Visual Questions from Blind People)",b633e14aa084fab57f20ad0b4612e0932ae1f2dc,15394669439,6,0,101,1535060843,1599249507
Dataset,"Holistic Recognition of Low Quality License Plates (HDR dataset)",8ed33d02d6b36c389dd077ea2478cc83ad117ef3,65883722,7,0,1877,1535604401,1599249372
Dataset,"MoNuSeg Training Data - Multi-organ nuclei segmentation from H&E stained histopathological images",c87688437fb416f66eecbd8c419aba00dd12997f,142306116,8,0,191,1536186326,1599249653
Dataset,"Medical Segmentation Decathlon Datasets",274be65156ed14828fb7b30b82407a2417e1924a,75906970628,8,0,270,1537440844,1599249660
Dataset,"Non-contrast head/brain CT CQ500 Dataset",47e9d8aab761e75fd0a81982fa62bddf3a173831,28660285880,11,1,7178,1538754509,1662662330
Dataset,"comma.ai driving dataset",58c41e8bcc8eb4e2204a3b263cdf728c0a7331eb,48284827648,5,0,455,1540484528,1599249425
Dataset,"ImageClef - IAPR TC-12 Benchmark",cf870b196222cf961a01c13999be9e4b7760cef1,1764963259,4,0,50,1541274418,1673994196
Dataset,"BRATS2013 Tumor-NoTumor Dataset (T-NT)",d52ccc21455c7a82fd6e58964c89b7da99e0edf7,65630646,8,0,1992,1541393360,1599249382
Dataset,"POLEN23E: image dataset for the Brazilian Savannah pollen types",ee51ec7708b35b023caba4230c871ae1fa254ab3,34561190,6,0,138,1541729016,1599249393
Dataset,"The PatchCamelyon benchmark dataset (PCAM)",1561a180b11d4b746273b5ce46772ad36f1229b6,8061211742,7,0,110,1542118185,1599249439
Dataset,"Indiana University - Chest X-Rays (XML Reports)",66450ba52ba3f83fbf82ef9c91f2bde0e845aba9,1112632,24,0,26642,1542900896,1599249262
Dataset,"Indiana University - Chest X-Rays (PNG Images)",5a3a439df24931f410fac269b87b050203d9467d,1360814128,23,0,24224,1542902411,1599249484
Dataset,"30M Factoid Question-Answer Corpus (30MQA)",973fb709bdb9db6066213bbc5529482a190098ce,529342167,10,0,2541,1543460417,1650839624
Dataset,"Chest X-Ray Images (Pediatric Pneumonia)",7208a86910cc518ae8feaa9021bf7f8565b97644,1236184657,8,0,3439,1544813267,1608582614
Dataset,"Labeled Optical Coherence Tomography (OCT)",198145c88af9a1d61ba8070f5b05c3539896ff4e,5793183169,9,0,131,1544896873,1599249653
Dataset,"Condensing Steam: Distilling the Diversity of Gamer Behavior",eba3b48fcdaa9e69a927051f1678251a86a546f3,18302328983,4,0,258,1547577949,1599249202
Dataset,"DeepLesion (10,594 CT scans with lesions)",de50f4d4aa3d028944647a56199c07f5fa6030ff,243037288033,11,4,2045,1548522158,1599249611
Dataset,"ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events",c5bf370a90cae548d5a306c1be7d79186b9f60b9,1652894362654,2,3,59,1549395122,1599215294
Dataset,"Kaggle Diabetic Retinopathy Detection Training Dataset (DRD)",08c244595c6cc4ec403b21023cf99c2b085cbc72,34999421799,8,0,2348,1549431917,1599249546
Dataset,"IDRiD (Indian Diabetic Retinopathy Image Dataset)",3bb974ffdad31f9df9d26a63ed2aea2f1d789405,1010096056,12,0,15693,1549438671,1599249494
Dataset,"ImageNet Large Scale Visual Recognition Challenge (V2017)",943977d8c96892d24237638335e481f3ccd54cfb,166022728827,8,0,3420,1551893373,1599249269
Dataset,"Lung CT Segmentation Challenge 2017 (LCTSC)",0a3611528c9172383656cb1b6a07cfb7f095eb82,5108773000,8,0,1063,1553268148,1599249635
Dataset,"PADCHEST_SJ (Feb 2019 Update)",dec12db21d57e158f78621f06dcbe78248d14850,1127527483252,6,1,124,1554602843,1599249622
Dataset,"UCF Google Street View Dataset 2014",e52a8978af7c2f734f2b30795075dbcd50efc983,46247776646,5,0,121,1554934764,1599249516
Dataset,"Head-Neck-CT",d06aafd957f0c8c9b0eb4636e5c3ebdb7bdaf54f,22836341441,8,0,273,1555876335,1599249545
Dataset,"PROSTATEx",5a447ff50062194bd58dd11c0fedead59e6d873c,4324268308,7,0,622,1556387716,1599249654
Dataset,"Inria Aerial Image Labeling Dataset",cf445f6073540af0803ee345f46294f088e7bba5,20957265875,7,0,230,1556389758,1599249517
Dataset,"Stanford Drone Dataset",01f95ea32e160e6c251ea55a87bd5a24b23cb03d,71002113639,11,0,524,1556390884,1599249523
Dataset,"CMU Graphics Lab Motion Capture Database Converted to FBX",8e21416d1584981ef3e9d8a97ee4278f93390623,1917480550,3,0,921,1558028790,1599249636
Dataset,"MIT-BIH Arrhythmia Database",78d14c9cb4fa765b3c323c1a26bd114e2b30ef34,93861490,8,0,265,1559159458,1599249668
Dataset,"OpenWebText (Gokaslan's distribution, 2019), GPT-2 Tokenized",36c39b25657ce1639ccec0a91cf242b42e1f01db,16023403913,3,0,195,1559409558,1599249652
Dataset,"MS-Celeb-1M: {A} Dataset and Benchmark for Large-Scale Face Recognition",9e67eb7cc23c9417f39778a8e06cca5e26196a97,246390693904,9,0,4824,1559654381,1606793192
Dataset,"DiaRetDB1 V2.1 - Diabetic Retinopathy Database",817b91fd639263f6f644de4ccc9575c20b005c6c,144096332,12,0,6691,1559702718,1599249659
Dataset,"DRIMDB (Diabetic Retinopathy Images Database) Database for Quality Testing of Retinal Images",99811ba62918f8e73791d21be29dcc372d660305,17074713,9,0,5316,1559703679,1599249177
Dataset,"r/WritingPrompts, Text (2018)",b4fa678ca4a330cf7078750b93eaefb1680a9053,87467308,4,0,370,1560962093,1599249657
Dataset,"ISIC2018: Skin Lesion Analysis Towards Melanoma Detection",1e3811b66f1129a2b86b7c291316db8583dbc94f,17082696680,7,0,467,1563983307,1599249655
Dataset,"P. vivax (malaria) infected human blood smears (BBBC041)",2fed90eeaa0fbf98aba474c5d7e56f6290121507,2259224287,8,0,288,1564717065,1599249390
Dataset,"Twitch Emotes Images Dataset",168649d9e29662e033d8db9c7bf0077c793d36c8,4286330880,7,0,543,1564840702,1599249652
Dataset,"Minecraft Skins",14cf27fca7f26714d2a5193dc95348a4712cdcdf,2471638528,6,0,914,1564996988,1599249629
Dataset,"MRI Dataset for Hippocampus Segmentation (HFH) (hippseg_2011)",d019f4f082f3fda94f0f74577b50dc30beee7bf8,598881636,7,0,731,1566309314,1599249636
Dataset,"1000 Fundus images with 39 categories",6d239d7d6c23f8b2a8046cca7078a7e10c6889d0,402759715,8,0,1118,1566312641,1599249667
Dataset,"Replicated GPT-2 1.5B Parameter Model",af468cfbb0284a35e706f5ae9b5dbcb45684f9d2,5787581694,4,0,1117,1566686231,1599249667
Dataset,"Ocular Disease Intelligent Recognition ODIR-5K",cf3b8d5ecdd4284eb9b3a80fcfe9b1d621548f72,1300482376,13,0,7668,1574709667,1599249173
Dataset,"musicnet.tar.gz",d2b2ae5e3ec4fd475d6e4c517d4c8752a7aa8455,11097394998,3,0,292,1575349774,1599249485
Dataset,"Illinois DOC labeled faces dataset",4b9b7e449aa732842aea1a7d4e6413f4507aea99,6362542606,6,0,234,1575580155,1599249209
Dataset,"LNDb CT scan dataset (training)",e3c196b07c8ea94ac5fca872bccf2cc035f4e88d,29209516876,8,0,242,1576518921,1599249658
Dataset,"RSNA Pneumonia Detection Challenge (JPG files)",95588a735c9ae4d123f3ca408e56570409bcf2a9,3928285701,10,0,1337,1584592477,1621614861
Dataset,"TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild",1faf1b53cc0099d2206f02be42b5688952c3c6b3,1138275041195,1,1,51,1587326170,1599249657
Dataset,"PMC Open Access Subset",06d6badd7d1b0cfee00081c28fddd5e15e106165,84144856912,8,0,221,1590288023,1599249672
Dataset,"Leaf counting dataset",a147c27ea0a9c155df9d77af832c321210cf5529,925394199,5,0,168,1592867649,1599249546
Dataset,"SIIM-ACR Pneumothorax Segmentation",6ef7c6d039e85152c4d0f31d83fa70edc4aba088,2072340626,7,0,802,1593828455,1666141512
Dataset,"Sci-Hub SQL Database (2020-05-30)",4b13244559282f9650a382f70506dc4c516215e2,10352938638,9,1,2540,1594131932,1599249660
Dataset,"Object-CXR - Automatic detection of foreign objects on chest X-rays",fdc91f11d7010f7259a05403fc9d00079a09f5d5,13636253487,8,0,1296,1594238373,1652304529
Dataset,"DRIVE: Digital Retinal Images for Vessel Extraction",062dc18f55b086c76c718ac88f98972789b3c04c,29343870,15,0,20218,1594504912,1599249170
Dataset,"Great Zebra and Giraffe Count ID Dataset",69160c6bf11275321017f18124dbaff2d381b21c,10433199738,6,0,192,1596173060,1606847052
Dataset,"Whale Shark ID Dataset",bb47cd1d6dde2f49b040495382c778c102409080,6466072650,5,1,120,1596173199,1606793162
Dataset,"PanNuke: An Open Pan-Cancer Histology Dataset for Nuclei Instance Segmentation and Classification",99f2c7b57b95500711e33f2ee4d14c9fd7c7366c,2077087715,9,0,460,1597377637,1599249617
Dataset,"UT Zappos50K (Version 2.1)",3b3cb58f4ccafc6320d06d00f0862a4ba923b510,887031043,5,0,116,1602861130,1602955126
Dataset,"TB Portal Tuberculosis Chest X-ray dataset for Belarus",509f986b456b6fce04c15f9d1de22cd4ccb2c4b7,12398871154,8,0,394,1603339369,1606928930
Dataset,"115 paintings from the Hermitage museum, high-resolution, JPEG",0ef42919a5688ea60f7174ccf899a91774508b48,2233151877,32,1,14646,1611854250,1611854250
Dataset,"10 years of Dukascopy Forex Tick Data (2008-2019)",8baee145786f4311b66bea5d13ef30eedce04a24,65032104495,5,1,595,1613875273,1613875273
Dataset,"NASA Astronomy Picture of the Day Archive (7800 images, 2011)",5f755e078ee9195b8ae0b3336710e6ce92ef3251,2816870400,13,0,1868,1614032721,1614032721
Dataset,"Breast Ultrasound Images Dataset (Dataset BUSI)",d0b7b7ae40610bbeaea385aeb51658f527c86a16,205873341,12,0,4900,1614983926,1673902907
Dataset,"Vggface2: A dataset for recognising faces across pose and age",535113b8395832f09121bc53ac85d7bc8ef6fa5b,40249987403,37,1,19094,1615161497,1676964588
Dataset,"Ukrainian Open Speech To Text Dataset 4.2 ~1200 hours",fcf8bb60c59e9eb583df003d54ed61776650beb8,188307794768,0,0,6,1615285367,1615316440
Dataset,"COCO 2017 Resized to 256x256",eea5a532dd69de7ff93d5d9c579eac55a41cb700,1643933412,8,0,670,1617633762,1617633940
Dataset,"Reading Text in the Wild with Convolutional Neural Networks",3d0b4f09080703d2a9c6be50715b46389fdb3af1,10678411583,47,1,32618,1636733886,1671897198
Dataset,"Synthetic Data for Text Localisation in Natural Images",2dba9518166cbd141534cbf381aa3e99a087e83c,73499997703,14,0,3212,1637015900,1637687626
Dataset,"The New York Times Annotated Corpus",a48d52cbb929b7e2a601dcc1e48a30d0f16284ca,3231375069,15,1,2846,1656658660,1659932707
Dataset,"OntoNotes 5.0 Annotated Text Corpus LDC2013T19",677c372dc782db9ecfda7284a2fe48d925e7fc4c,839107814,3,0,335,1656786238,1659932699
Dataset,"DARPA TIMIT Acoustic-Phonetic Continuous Speech Corpus LDC93S1",dbb2c90ad66f5ca3e460889b2fd5cbbda6680372,385521854,3,0,2701,1656787321,1659932690
Dataset,"TAC KBP Entity Discovery and Linking - Comprehensive Training and Evaluation Data LDC2019T02",69d99dffac95e764bdf4bd21bef1c059116cbc3e,20356702766,2,0,78,1656985893,1659932720
Dataset,"BOLT Egyptian Arabic Treebank Conversational Telephone Speech NLP LDC2021T12",65e7183bec20d506c07be8f708a403da21b2ddcb,19422186,4,0,41,1657522155,1659932731
Dataset,"Abstract Meaning Representation AMR Annotation Release 3.0 LDC2017T10",93a630f12f28b824b7983f990f60d6568ea0c5a7,38823861,5,0,144,1657523455,1659932736
Dataset,"English Gigaword 5th edition LDC2011T07",26ee332f46d4e4029fa978052a4ba3eabf2da70c,9759541171,6,0,327,1657588054,1659932664
Dataset,"Chinese Gigaword 5th edition LDC2011T13",3154947ad1bc51b82d616b58aecb0de0c993a837,4387118896,3,0,90,1657597407,1659932656
Dataset,"French Gigaword 3rd edition LDC2011T10",ddec3ec99160eb48c0d18781361bfbd4c0707451,2082167617,5,1,1824,1657663035,1659932647
Dataset,"Spanish Gigaword 3rd edition LDC2011T12",ad46237d6f4836442cfc4decfe10535da1ce8efd,2776654691,2,0,76,1657665825,1659932638
Dataset,"TAC KBP Comprehensive English Source Corpora LDC2018T03",17f9243ce6286e3daae77469ad89e44040fa3a05,6798478390,3,0,68,1657669000,1659932755
Dataset,"Reddit comments/submissions 2005-06 to 2022-06",0e1813622b3f31570cfe9a6ad3ee8dabffdb8eb6,1759433926547,4,0,187,1658085561,1705030690
Dataset,"The Oxford-IIIT Pet Dataset",b18bbd9ba03d50b0f7f479acc9f4228a408cecc1,811092049,116,0,44501,1659087709,1659985761
Dataset,"The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions",dc3188ee1ce7e2d2254113111b406c484101ba65,3203576126,8,0,189,1659117309,1659985748
Dataset,"INbreast: toward a full-field digital mammographic database",ce1ecade37814701ac95193a910a3c6917ea43b3,2063601019,11,0,2045,1659758699,1659985713
Dataset,"TotalSegmentator CT Dataset",337819f0e83a1c1ac1b7262385609dad5d485abf,28404091806,9,0,132,1668702250,1702320852
Dataset,"Data of the White Matter Hyperintensity (WMH) Segmentation Challenge",a6d90ae5a9ff4cc8184f122048495fd6bd18d6ba,8715128611,8,0,66,1671649290,1671651576
Dataset,"STructured Analysis of the Retina",e4554cd63400dc13b74477efe98032c10757c269,484369267,8,0,897,1672519413,1674332133
Dataset,"HMC-QU echocardiography ultrasound recordings",11832dbd0b58c1dd9305a10373c9536872dd31af,2492458234,11,0,935,1673108668,1673109574
Dataset,"CAMUS Cardiac Acquisitions for Multi-structure Ultrasound Segmentation",ae545c1e3ce045c33942f89e67f618a6439104a6,3833291884,11,0,519,1673564487,1673565157
Course,"CS231n: Convolutional Neural Networks Spring 2017",ed8a16ebb346e14119a03371665306609e485f13,2625171165,17,0,26879,1537902798,1599249664
Course,"University of Washington - Pedro Domingos - Machine Learning",0db676a6aaff8c33f9749d5f9c0fa22bf336bc76,9066763048,15,0,10741,1541763365,1599249594
Course,"Tom Mitchell - Machine Learning - 2012",35b6b8bf0c2931ba7ecd8a1a8e65fa32f3e7473f,5866402365,11,0,6231,1542565512,1599249259
Course,"01QZP 2018-2019 Ambient Intelligence",9bbe28468af204ccefe75662cd184ce0abed0ad4,4378944634,5,0,6178,1560426761,1599249662
Course,"[Coursera] What A Plant Knows (Daniel Chamovitz, Tel Aviv University)",81ff5fc1df7c1fb9300e9712368dfc479427004d,538937350,12,0,15051,1591709042,1599249562
Course,"Medical Imaging with Deep Learning Tutorial 2020 - Joseph Paul Cohen",e0974c84449826e34d8cc96c943cba2af18ab514,76859393,18,0,8473,1595950639,1599249669